A Joint Channel Estimation and Compression Method Based on GAN in 6G Communication Systems

Author:

Du Ying12ORCID,Li Yang2ORCID,Xu Mingfeng2,Jiang Jiamo2ORCID,Wang Weidong1

Affiliation:

1. Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230052, China

2. Mobile Communications Innovation Center, China Academy of Information and Communications Technology, Beijing 100191, China

Abstract

Due to the increasing popularity of communication devices and vehicles, the channel environment becomes more and more complex, which makes conventional channel estimation methods further increase the pilot overhead to maintain estimation performance. However, it declines the throughput of communication networks. In this paper, we provide a novel two-stage based channel estimation method by using generative adversarial networks (GANs) to handle this problem in orthogonal frequency division multiplexing (OFDM) systems. Specifically, the first stage aims to learn the mapping from a low-dimensional latent variable to the real channel sample. During the second stage, an iterative algorithm method is designed to find the optimal latent variable by matching the pilot channels of a real channel and generated channel. Then, the data channels are recovered based on the learned mapping relationship between the latent variable and the real channel sample. The simulation results show that our proposed method can achieve a performance gain of more than 2 dB with a pilot reduction by 75% when SNR is 10 dB, by comparing with the widely used Wiener filter interpolation method. In addition, as the low-dimensional latent variable can be obtained simultaneously, it can also be used for reducing the feedback overhead.

Funder

the National Key R&D Program of China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing 6G network security: GANs for pilot contamination attack detection in massive MIMO systems;AEU - International Journal of Electronics and Communications;2024-02

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